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Title: High-performance and scalable on-chip digital Fourier transform spectroscopy

Abstract

On-chip spectrometers have the potential to offer dramatic size, weight, and power advantages over conventional benchtop instruments for many applications such as spectroscopic sensing, optical network performance monitoring, hyperspectral imaging, and radio-frequency spectrum analysis. Existing on-chip spectrometer designs, however, are limited in spectral channel count and signal-to-noise ratio. Here we demonstrate a transformative on-chip digital Fourier transform spectrometer that acquires high-resolution spectra via time-domain modulation of a reconfigurable Mach-Zehnder interferometer. The device, fabricated and packaged using industry-standard silicon photonics technology, claims the multiplex advantage to dramatically boost the signal-to-noise ratio and unprecedented scalability capable of addressing exponentially increasing numbers of spectral channels. As a result, we further explore and implement machine learning regularization techniques to spectrum reconstruction. Using an ‘elastic-D 1’ regularized regression method that we develop, we achieved significant noise suppression for both broad (>600 GHz) and narrow (<25 GHz) spectral features, as well as spectral resolution enhancement beyond the classical Rayleigh criterion.

Authors:
ORCiD logo [1];  [1];  [1];  [1];  [1]; ORCiD logo [1];  [1];  [1]
  1. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Publication Date:
Research Org.:
Univ. of Delaware, Newark, DE (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1483941
Grant/Contract Number:  
NA0002509
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Nature Communications
Additional Journal Information:
Journal Volume: 9; Journal Issue: 1; Journal ID: ISSN 2041-1723
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
47 OTHER INSTRUMENTATION

Citation Formats

Kita, Derek M., Miranda, Brando, Favela, David, Bono, David, Michon, Jérôme, Lin, Hongtao, Gu, Tian, and Hu, Juejun. High-performance and scalable on-chip digital Fourier transform spectroscopy. United States: N. p., 2018. Web. doi:10.1038/s41467-018-06773-2.
Kita, Derek M., Miranda, Brando, Favela, David, Bono, David, Michon, Jérôme, Lin, Hongtao, Gu, Tian, & Hu, Juejun. High-performance and scalable on-chip digital Fourier transform spectroscopy. United States. doi:10.1038/s41467-018-06773-2.
Kita, Derek M., Miranda, Brando, Favela, David, Bono, David, Michon, Jérôme, Lin, Hongtao, Gu, Tian, and Hu, Juejun. Tue . "High-performance and scalable on-chip digital Fourier transform spectroscopy". United States. doi:10.1038/s41467-018-06773-2. https://www.osti.gov/servlets/purl/1483941.
@article{osti_1483941,
title = {High-performance and scalable on-chip digital Fourier transform spectroscopy},
author = {Kita, Derek M. and Miranda, Brando and Favela, David and Bono, David and Michon, Jérôme and Lin, Hongtao and Gu, Tian and Hu, Juejun},
abstractNote = {On-chip spectrometers have the potential to offer dramatic size, weight, and power advantages over conventional benchtop instruments for many applications such as spectroscopic sensing, optical network performance monitoring, hyperspectral imaging, and radio-frequency spectrum analysis. Existing on-chip spectrometer designs, however, are limited in spectral channel count and signal-to-noise ratio. Here we demonstrate a transformative on-chip digital Fourier transform spectrometer that acquires high-resolution spectra via time-domain modulation of a reconfigurable Mach-Zehnder interferometer. The device, fabricated and packaged using industry-standard silicon photonics technology, claims the multiplex advantage to dramatically boost the signal-to-noise ratio and unprecedented scalability capable of addressing exponentially increasing numbers of spectral channels. As a result, we further explore and implement machine learning regularization techniques to spectrum reconstruction. Using an ‘elastic-D1’ regularized regression method that we develop, we achieved significant noise suppression for both broad (>600 GHz) and narrow (<25 GHz) spectral features, as well as spectral resolution enhancement beyond the classical Rayleigh criterion.},
doi = {10.1038/s41467-018-06773-2},
journal = {Nature Communications},
issn = {2041-1723},
number = 1,
volume = 9,
place = {United States},
year = {2018},
month = {10}
}

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Cited by: 23 works
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    Works referencing / citing this record:

    Single-nanowire spectrometers
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    Single-nanowire spectrometers
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